Antispam: online checks no longer switch off Bayes; replies teach ham

- The "online reputation checks" rspamd profile used groups_enabled,
  which means ONLY those groups: with the switch on, a message got the
  RBL lookups alone (1 rule instead of 19, score 0.00) and Bayes never
  ran, so every spam lesson was ignored. It now disables nothing.
- A reply or reply-all teaches the answered message as ham (not
  forwards or new mail, not one's own Sent/Drafts, never over an
  explicit spam mark; once per message). message.sent now carries the
  draft's kind and reply_to_message_id.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>

plugins/webmail_plugin_antispam/webmail_plugin_antispam/__init__.py

@@ -23,6 +23,7 @@ from webmail_plugin_antispam.hook import (
     on_account_state_changed,
     on_message_changed,
     on_message_new,
+    on_message_sent,
 )
 from webmail_plugin_antispam.jobs import bootstrap_account, bootstrap_sweep
 from webmail_plugin_antispam.router import router
@@ -37,6 +38,8 @@ plugin = Plugin(
         "message.new": on_message_new,
         # Passive learning: where the user files things teaches the filter (§C.5).
         "message.changed": on_message_changed,
+        # ... and so does what the user answers: a reply teaches "not spam".
+        "message.sent": on_message_sent,
         # An account going live is the cue to warm Bayes from its history (§C.5).
         "account.state_changed": on_account_state_changed,
     },

plugins/webmail_plugin_antispam/webmail_plugin_antispam/hook.py

@@ -223,6 +223,40 @@ async def on_message_changed(payload: dict[str, Any]) -> None:
     )
 
 
+async def on_message_sent(payload: dict[str, Any]) -> None:
+    """Passive learning from replies: answering a message says it was wanted.
+
+    Only real replies (not forwards — forwarding a scam to warn someone is the
+    opposite of wanting it — and not new mail), to mail someone sent the user
+    (not their own, in Sent or Drafts). A message the user marked as spam
+    stays spam: an explicit verdict outranks this one. Taught once.
+    """
+    if payload.get("kind") not in ("reply", "reply_all"):
+        return
+    uid_raw, mid_raw = payload.get("user_id"), payload.get("reply_to_message_id")
+    if not isinstance(uid_raw, str) or not isinstance(mid_raw, str):
+        return
+    user_id, message_id = uuid.UUID(uid_raw), uuid.UUID(mid_raw)
+    if await _already_learned(user_id, message_id) in ("ham", "spam"):
+        return
+
+    env = await _SDK.messages.envelope(user_id, message_id)
+    if env is None or env.get("mailbox_special_use") in ("sent", "drafts"):
+        return
+    settings = await policy.load_settings(user_id)
+    if not settings.covers(str(env.get("account_id") or "")):
+        return
+    raw = await _SDK.messages.raw(user_id, message_id)
+    if raw is None or not await rspamd.learn(raw, user_key=str(user_id), spam=False):
+        return  # engine down: unrecorded, a later lesson may still teach it
+
+    await _remember_learned(user_id, message_id, verdict="ham", action="none")
+    await _SDK.publish(
+        "plugin.antispam.learned",
+        {"user_id": str(user_id), "message_id": str(message_id), "verdict": "ham"},
+    )
+
+
 async def on_account_state_changed(payload: dict[str, Any]) -> None:
     """When an account finishes its initial import, warm Bayes from what it holds.